Progress of 1D protein structure prediction at last

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75 Scopus citations

Abstract

Accuracy of predicting protein secondary structure and solvent accessibility from sequence information has been improved significantly by using information contained in multiple sequence alignments as input to a neural 'network system. For the Asilomar meeting, predictions for 13 proteins were generated automatically using the publicly available prediction method PHD. The results confirm the estimate of 72% three‐state prediction accuracy. The fairly accurate predictions of secondary structure segments made the tool useful as a starting point for modeling of higher dimensional aspects of protein structure. © 1995 Wiley‐Liss, Inc.

Original languageEnglish
Pages (from-to)295-300
Number of pages6
JournalProteins: Structure, Function and Bioinformatics
Volume23
Issue number3
DOIs
StatePublished - Nov 1995
Externally publishedYes

Keywords

  • automatic prediction of protein secondary structure and solvent accessibility
  • neural networks

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